Low complexity partial selected mapping for PAPR reduction of OFDM system

International audienceWe present partial blind selected mapping method (P-BSLM) as a probabilistic OFDM-PAPR reduction method. The P-BSLM method generates more candidates than the classical SLM (C-SLM) method while using the same number of IFFT computations. Moreover, common stage computation in an IFFT process can reduce the computational complexity. More candidates increase the PAPR reduction capability, and give a better error performance in the presence of non-linear amplifier. This method has the maximum spectral efficiency without side information, and the phase sequence can be correctly detected using partial blind phase sequence detection

A joint OFDM PAPR reduction and data decoding scheme with no SI estimation

The need for side information (SI) estimation poses a major challenge when selected mapping (SLM) is implemented to reduce peak-to-average power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) systems. Recent studies on pilot-assisted SI estimation procedures suggest that it is possible to determine the SI without the need for SI transmission. However, SI estimation adds to computational complexity and implementation challenges of practical SLM-OFDM receivers. To address these technical issues, this paper presents the use of a pilot-assisted cluster-based phase modulation and demodulation procedure called embedded coded modulation (ECM). The ECM technique uses a slightly modified SLM approach to reduce PAPR and to enable data recovery with no SI transmission and no SI estimation. In the presence of some non-linear amplifier distortion, it is shown that the ECM method achieves similar data decoding performance as conventional SLM-OFDM receiver that assumed a perfectly known SI and when the SI is estimated using a frequency-domain correlation approach. However, when the number of OFDM subcarriers is small and due to the clustering in ECM, the modified SLM produces a smaller PAPR reduction gain compared with conventional SLM

Enhancement of Selective Mapping Technique for Peak-To-Average Power Ratio Reduction in OFDM using Normalized Hilbert Matrix

Orthogonal Frequency Division Multiplexing (OFDM) is good multicarrier transmission system used for broadband wireless communication systems owing to it is numerous benefits such as high bandwidth efficiency, high transmission rate, and robustness against multi path problem. However, one of the hitches of OFDM high Peak-to-Average Power Ratio (PAPR) of the transmitted signal, which results in signal distortion and reduced power amplifier efficiency. Selective Mapping (SLM) is attractive distortion less method for PAPR reduction. The performance of this technique in reducing the PAPR is largely affected by the magnitude of phase rotation vectors. It also requires to  transmit the selected phase rotation vectors that produce the signal with the lowest PAPR to the receiver end for the recovery of the original data. In this paper, two normalization procedures in conjunction with the Hilbert matrix are used to obtain phase rotation vectors for the SLM technique to further reduce the PAPR value. The reduction of PAPR is desirable in order to have a better power efficiency of the amplifier. The simulation results demonstrated that the enhanced SLM technique using normalized Hilbert matrix achieved a better PAPR reduction compared to SLM using Hilbert matrix without normalization with 14.0%, and 14.0%  percentage improvement. Another benefit of this method is that the matrix can be generated at the receiver end to obtain the data signal, thus eliminating the transmission of side information with the original data

Peak to average power ratio reduction in NC–OFDM systems

Non contiguous orthogonal frequency division multiplexing (NC-OFDM) is an efficient and adaptable multicarrier modulation scheme to be used in cognitive radio communications. However like OFDM, NC-OFDM also suffers from the main drawback of high peak to average power ratio (PAPR). In this paper PAPR has been reduced by employing three different trigonometric transforms. Discrete cosine transform (DCT), discrete sine transform (DST) and fractional fourier transform (FRFT) has been combined with conventional selected level mapping (SLM) technique to reduce the PAPR of both OFDM and NC-OFDM based systems. The method combines all the transforms with SLM in different ways. Transforms DCT, DST and FRFT have been applied before the SLM block or inside the SLM block before IFFT. Simulation results show the comparative analysis of all the transforms using SLM in case of both OFDM and NC-OFDM based systems

A low complexity SI sequence estimator for pilot-aided SLM–OFDM systems

Selected mapping (SLM) is a well-known method for reducing peak-to-average power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) systems. However, as a consequence of implementing SLM, OFDM receivers often require estimation of some side information (SI) in order to achieve successful data recovery. Existing SI estimation schemes have very high computational complexities that put additional constraints on limited resources and increase system complexity. To address this problem, an alternative SLM approach that facilitates estimation of SI in the form of phase detection is presented. Simulations show that this modified SLM approach produces similar PAPR reduction performance when compared to conventional SLM. With no amplifier distortion and in the presence of non-linear power amplifier distortion, the proposed SI estimation approach achieves similar data recovery performance as both standard SLM–OFDM (with perfect SI estimation) and also when SI estimation is implemented through the use of an existing frequency-domain correlation (FDC) decision metric. In addition, the proposed method significantly reduces computational complexity compared with the FDC scheme and an ML estimation scheme